shishishu/LLM-Inference-Acceleration

LLM Inference with Deep Learning Accelerator.

59

54 commits

updated Jan 23, 2025

See the code

README

LLM-Inference-Acceleration

Table of Contents

About This Project

This project is dedicated to collecting and curating research papers focused on Large Language Model (LLM) inference acceleration. I hope to summarize and share the knowledge I gain during my self-learning journey.

It will be updated regularly. Contributions are welcome, so feel free to star or submit a pull request.

Listing of Papers By Topics

Design Rule:

  • Keywords: frequent academic terms for paper search.
  • Paper intro: core idea/image with useful extensions are included for quick start. See example [intro of SmoothQuant].
  • Citation: data for the papers is sourced from Google Scholar.

Review

Last update of citation was on 28th July, 2024.

KeywordsTitlePaperAffiliationDateCitation
LLM InferenceTowards Efficient Generative Large Language Model Serving: A Survey from Algorithms to Systems[pdf] [intro]CMU2023.1236
LLM InferenceA survey on efficient inference for large language models[pdf] [intro]THU, Infinigence-AI, SJTU etc2024.0414

Attention Mechanism

Last update of citation was on 23rd Jan, 2025.

Upcoming topics include: FlashDecoding, QLoRA

KeywordsTitlePaperAffiliationDateCitation
MQAFast Transformer Decoding: One Write-Head is All You Need[pdf]Google2019.11340
GQAGQA: Training Generalized Multi-Query Transformer Models from Multi-Head Checkpoints [EMNLP 2023][pdf] [intro]Google2023.05489
ALiBiTrain Short, Test Long: Attention with Linear Biases Enables Input Length Extrapolation [ICLR 2022][pdf] [intro]UW, Facebook, Allen Institute2021.08605
RoPERoFormer: Enhanced Transformer with Rotary Position Embedding [Neurocomputing 2024][pdf] [intro]Zhuiyi Technology2021.041743
CoPEContextual Position Encoding: Learning to Count What's Important[pdf] [intro]Meta2024.0520
FlashAttentionFlashAttention: Fast and Memory-Efficient Exact Attention with IO-Awareness [NeurIPS 2022][pdf] [intro]Stanford, University at Buffalo2022.051658
FlashAttention2FlashAttention-2: Faster Attention with Better Parallelism and Work Partitioning[pdf] [intro]Princeton, Stanford2023.07706
LongformerLongformer: The Long-Document Transformer[pdf] [intro]Allen Institute2020.044577
MistralMistral 7B[pdf] [intro]Mistral2023.101151
StreamingLLM, Attention SinksEfficient Streaming Language Models with Attention Sinks [ICLR 2024][pdf] [intro]MIT, Meta, CMU etc2023.09386
LoRALoRA: Low-Rank Adaptation of Large Language Models [ICLR 2022][pdf] [intro]Microsoft2021.0610000
LISALISA: Layerwise Importance Sampling for Memory-Efficient Large Language Model Fine-Tuning[pdf] [intro]HKUST, UIUC2024.0316
HydraLoRAHydraLoRA: An Asymmetric LoRA Architecture for Efficient Fine-Tuning [NIPS 2024][pdf] [intro]University of Macau, University of Texas at Austin, Cambridge2024.048
MLADeepSeek-V2: A Strong, Economical, and Efficient Mixture-of-Experts Language Model[pdf] [intro]DeepSeek2024.0577
MFAMulti-matrix Factorization Attention[pdf] [intro]StepFun, THU, FDU etc2024.120
TPATensor Product Attention Is All You Need[pdf] [intro]THU2025.010

Quantization

Last update of citation was on 5th July, 2024.

Upcoming topics include: QLoRA

KeywordsTitlePaperAffiliationDateCitation
LLM.int8LLM.int8(): 8-bit Matrix Multiplication for Transformers at Scale [NeurIPS 2022][pdf] [intro]UW, Facebook, Hugging Face etc2022.08554
SmoothQuantSmoothQuant: Accurate and Efficient Post-Training Quantization for Large Language Models [ICML 2023][pdf] [intro]MIT, NVIDIA2022.11382
AWQAWQ: Activation-aware Weight Quantization for LLM Compression and Acceleration [MLSys 2024][pdf] [intro]MIT, SJTU, NVIDIA etc2023.06235
OneBitOneBit: Towards Extremely Low-bit Large Language Models[pdf] [intro]THU, HIT2024.024
OneBitThe Era of 1-bit LLMs: All Large Language Models are in 1.58 Bits[pdf] [intro]Microsoft, UCAS2024.0239

KV Cache

Last update of citation was on 25th July, 2024.

KeywordsTitlePaperAffiliationDateCitation
vLLM, PagedAttentionEfficient Memory Management for Large Language Model Serving with PagedAttention [SOSP 2023][pdf] [intro]UC Berkeley, Stanford, UC San Diego2023.09496

Continuous Batching

Last update of citation was on 5th August, 2024.

KeywordsTitlePaperAffiliationDateCitation
Cellular BatchingLow latency rnn inference with cellular batching [EuroSys 2018][pdf]THU, NYU2018.0497
ORCAOrca: A Distributed Serving System for Transformer-Based Generative Models [OSDI 2022][pdf] [intro]SNU, FriendliAI2022.07195
SARATHISARATHI: Efficient LLM Inference by Piggybacking Decodes with Chunked Prefills[pdf] [intro]Microsoft, GIT2023.0836

HW/SW Co-design

Framework/System/Architecture

More

Last update of citation was on 8th August, 2024.

KeywordsTitlePaperAffiliationDateCitation
Block TransformerBlock Transformer: Global-to-Local Language Modeling for Fast Inference[pdf] [intro]KAIST, LG, Google2024.062
TTTLearning to (Learn at Test Time): RNNs with Expressive Hidden States[pdf] [intro]Stanford, UC San Diego, UC Berkeley etc2024.073
LazyLLMLazyLLM: Dynamic Token Pruning for Efficient Long Context LLM Inference[pdf] [intro]Apple, Meta2024.07

Contributors

shishishu

54 commits

shishishu/LLM-Inference-Acceleration

LLM Inference with Deep Learning Accelerator.

59

54 commits

updated Jan 23, 2025

See the code

README

LLM-Inference-Acceleration

Table of Contents

About This Project

This project is dedicated to collecting and curating research papers focused on Large Language Model (LLM) inference acceleration. I hope to summarize and share the knowledge I gain during my self-learning journey.

It will be updated regularly. Contributions are welcome, so feel free to star or submit a pull request.

Listing of Papers By Topics

Design Rule:

  • Keywords: frequent academic terms for paper search.
  • Paper intro: core idea/image with useful extensions are included for quick start. See example [intro of SmoothQuant].
  • Citation: data for the papers is sourced from Google Scholar.

Review

Last update of citation was on 28th July, 2024.

KeywordsTitlePaperAffiliationDateCitation
LLM InferenceTowards Efficient Generative Large Language Model Serving: A Survey from Algorithms to Systems[pdf] [intro]CMU2023.1236
LLM InferenceA survey on efficient inference for large language models[pdf] [intro]THU, Infinigence-AI, SJTU etc2024.0414

Attention Mechanism

Last update of citation was on 23rd Jan, 2025.

Upcoming topics include: FlashDecoding, QLoRA

KeywordsTitlePaperAffiliationDateCitation
MQAFast Transformer Decoding: One Write-Head is All You Need[pdf]Google2019.11340
GQAGQA: Training Generalized Multi-Query Transformer Models from Multi-Head Checkpoints [EMNLP 2023][pdf] [intro]Google2023.05489
ALiBiTrain Short, Test Long: Attention with Linear Biases Enables Input Length Extrapolation [ICLR 2022][pdf] [intro]UW, Facebook, Allen Institute2021.08605
RoPERoFormer: Enhanced Transformer with Rotary Position Embedding [Neurocomputing 2024][pdf] [intro]Zhuiyi Technology2021.041743
CoPEContextual Position Encoding: Learning to Count What's Important[pdf] [intro]Meta2024.0520
FlashAttentionFlashAttention: Fast and Memory-Efficient Exact Attention with IO-Awareness [NeurIPS 2022][pdf] [intro]Stanford, University at Buffalo2022.051658
FlashAttention2FlashAttention-2: Faster Attention with Better Parallelism and Work Partitioning[pdf] [intro]Princeton, Stanford2023.07706
LongformerLongformer: The Long-Document Transformer[pdf] [intro]Allen Institute2020.044577
MistralMistral 7B[pdf] [intro]Mistral2023.101151
StreamingLLM, Attention SinksEfficient Streaming Language Models with Attention Sinks [ICLR 2024][pdf] [intro]MIT, Meta, CMU etc2023.09386
LoRALoRA: Low-Rank Adaptation of Large Language Models [ICLR 2022][pdf] [intro]Microsoft2021.0610000
LISALISA: Layerwise Importance Sampling for Memory-Efficient Large Language Model Fine-Tuning[pdf] [intro]HKUST, UIUC2024.0316
HydraLoRAHydraLoRA: An Asymmetric LoRA Architecture for Efficient Fine-Tuning [NIPS 2024][pdf] [intro]University of Macau, University of Texas at Austin, Cambridge2024.048
MLADeepSeek-V2: A Strong, Economical, and Efficient Mixture-of-Experts Language Model[pdf] [intro]DeepSeek2024.0577
MFAMulti-matrix Factorization Attention[pdf] [intro]StepFun, THU, FDU etc2024.120
TPATensor Product Attention Is All You Need[pdf] [intro]THU2025.010

Quantization

Last update of citation was on 5th July, 2024.

Upcoming topics include: QLoRA

KeywordsTitlePaperAffiliationDateCitation
LLM.int8LLM.int8(): 8-bit Matrix Multiplication for Transformers at Scale [NeurIPS 2022][pdf] [intro]UW, Facebook, Hugging Face etc2022.08554
SmoothQuantSmoothQuant: Accurate and Efficient Post-Training Quantization for Large Language Models [ICML 2023][pdf] [intro]MIT, NVIDIA2022.11382
AWQAWQ: Activation-aware Weight Quantization for LLM Compression and Acceleration [MLSys 2024][pdf] [intro]MIT, SJTU, NVIDIA etc2023.06235
OneBitOneBit: Towards Extremely Low-bit Large Language Models[pdf] [intro]THU, HIT2024.024
OneBitThe Era of 1-bit LLMs: All Large Language Models are in 1.58 Bits[pdf] [intro]Microsoft, UCAS2024.0239

KV Cache

Last update of citation was on 25th July, 2024.

KeywordsTitlePaperAffiliationDateCitation
vLLM, PagedAttentionEfficient Memory Management for Large Language Model Serving with PagedAttention [SOSP 2023][pdf] [intro]UC Berkeley, Stanford, UC San Diego2023.09496

Continuous Batching

Last update of citation was on 5th August, 2024.

KeywordsTitlePaperAffiliationDateCitation
Cellular BatchingLow latency rnn inference with cellular batching [EuroSys 2018][pdf]THU, NYU2018.0497
ORCAOrca: A Distributed Serving System for Transformer-Based Generative Models [OSDI 2022][pdf] [intro]SNU, FriendliAI2022.07195
SARATHISARATHI: Efficient LLM Inference by Piggybacking Decodes with Chunked Prefills[pdf] [intro]Microsoft, GIT2023.0836

HW/SW Co-design

Framework/System/Architecture

More

Last update of citation was on 8th August, 2024.

KeywordsTitlePaperAffiliationDateCitation
Block TransformerBlock Transformer: Global-to-Local Language Modeling for Fast Inference[pdf] [intro]KAIST, LG, Google2024.062
TTTLearning to (Learn at Test Time): RNNs with Expressive Hidden States[pdf] [intro]Stanford, UC San Diego, UC Berkeley etc2024.073
LazyLLMLazyLLM: Dynamic Token Pruning for Efficient Long Context LLM Inference[pdf] [intro]Apple, Meta2024.07

Contributors

shishishu

54 commits